{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import matplotlib.dates as mdates\n",
    "import rpy2.robjects as robjects\n",
    "\n",
    "from common_tools import r_import_tool as r_in\n",
    "from common_tools import plotting_tools as ploto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "robjects.r['load']('./data/d_sol_cw_w_in.RData')\n",
    "\n",
    "raw_data = r_in.import_rdata('d_sol_cw',0,'rawdata')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "robjects.r['load']('./data/modeldata_m1_out.RData')\n",
    "\n",
    "model_m1_s1 = r_in.import_rdata('data_m1',1,'m1')\n",
    "model_m2_s1 = r_in.import_rdata('data_m2',1,'m2')\n",
    "model_m3_s1 = r_in.import_rdata('data_m3',1,'m3')\n",
    "\n",
    "robjects.r['load']('./data/modeldata_m2_out.RData')\n",
    "\n",
    "model_m1_s2 = r_in.import_rdata('data_m1',1,'m1')\n",
    "model_m2_s2 = r_in.import_rdata('data_m2',1,'m2')\n",
    "model_m3_s2 = r_in.import_rdata('data_m3',1,'m3')\n",
    "\n",
    "robjects.r['load']('./data/modeldata_m3_out.RData')\n",
    "\n",
    "model_m1_s3 = r_in.import_rdata('data_m1',1,'m1')\n",
    "model_m2_s3 = r_in.import_rdata('data_m2',1,'m2')\n",
    "model_m3_s3 = r_in.import_rdata('data_m3',1,'m3')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create Panda datevectors and vector with week numbers\n",
    "raw_data['Time'] = pd.to_datetime(raw_data['Time'], unit='s') \n",
    "# raw_data['Week'] = raw_data['Time'].dt.week\n",
    "\n",
    "custom = {\"grid.linestyle\": \"dashed\", \"grid.color\": \"lightgrey\"}\n",
    "sns.set_theme(style=\"ticks\", rc = custom)\n",
    "palette = sns.color_palette(\"mako\")\n",
    "\n",
    "raw_data['num_data_points'] = range(0, len(raw_data['C_MW']))\n",
    "\n",
    "f, ax1 = plt.subplots(figsize=(3.5, 1.75))\n",
    "\n",
    "ax1 = sns.lineplot(x='Time', y='C_MW', data=raw_data, color=palette[2], linewidth=1)\n",
    "ax1.set_ylabel('$C_{MW}^{(i)}$ [pg/L]')\n",
    "ax1.set_xlabel('Date')\n",
    "ax1.grid(True) \n",
    "\n",
    "ax1.xaxis.set_major_formatter(mdates.DateFormatter('%m-%d')) # Format x-axis dates to mm-dd\n",
    "plt.xticks(raw_data['Time'][::1000], rotation=-60, ha='left')  # Adjust rotation and ha as needed\n",
    "\n",
    "# Set y-axis limits and custom ticks\n",
    "ax1.set_ylim(-0.5, 5.5)\n",
    "ax1.set_yticks([0, 2.5, 5])\n",
    "\n",
    "#plt.yticks(ticks=[2,5])\n",
    "plt.subplots_adjust(bottom=0.5)\n",
    "plt.subplots_adjust(left=0.25)\n",
    "plt.savefig(\"C_MW_plot_m2.pdf\", format='pdf')\n",
    "plt.show()\n",
    "\n",
    "f, ax2 = plt.subplots(figsize=(3.5, 1.75))\n",
    "\n",
    "ax2 = sns.lineplot(x='Time', y='Sol', data=raw_data, color=palette[3], linewidth=1)\n",
    "ax2.set_ylabel('$Sol$ [W/m$^2$]')\n",
    "ax2.set_xlabel('Date')\n",
    "ax2.grid(True)\n",
    "\n",
    "ax2.xaxis.set_major_formatter(mdates.DateFormatter('%m-%d')) # Format x-axis dates to mm-dd\n",
    "plt.xticks(raw_data['Time'][::1000], rotation=-60, ha='left')  # Adjust rotation and ha as needed\n",
    "\n",
    "# Set y-axis limits and custom ticks\n",
    "ax2.set_ylim(-50, 850)\n",
    "ax2.set_yticks([0, 250, 750])\n",
    "\n",
    "#plt.yticks(ticks=[500])\n",
    "plt.subplots_adjust(bottom=0.5)\n",
    "plt.subplots_adjust(left=0.25)\n",
    "plt.savefig(\"Sol_plot.pdf\", format='pdf')\n",
    "plt.show()\n",
    "\n",
    "f, ax3 = plt.subplots(figsize=(3.5, 1.75))\n",
    "\n",
    "ax3 = sns.lineplot(x='Time', y='T_S', data=raw_data, color=palette[4], linewidth=1)\n",
    "ax3.set_ylabel('$T_S$ [K]')\n",
    "ax3.set_xlabel('Date')\n",
    "ax3.grid(True)\n",
    "\n",
    "ax3.xaxis.set_major_formatter(mdates.DateFormatter('%m-%d')) # Format x-axis dates to mm-dd\n",
    "plt.xticks(raw_data['Time'][::1000], rotation=-60, ha='left')  # Adjust rotation and ha as needed\n",
    "\n",
    "# Set y-axis limits and custom ticks\n",
    "ax2.set_ylim(275, 295)\n",
    "ax2.set_yticks([280, 290])\n",
    "\n",
    "#plt.yticks(ticks=[10])\n",
    "plt.subplots_adjust(bottom=0.5)\n",
    "plt.subplots_adjust(left=0.25)\n",
    "plt.savefig(\"T_S_plot.pdf\", format='pdf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot resulting coefficient estimates for simulation data over all models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_palette = sns.color_palette(\"light:b\")\n",
    "\n",
    "# Create a palette dictionary matching the model names in the data\n",
    "palette = [total_palette[0], total_palette[2], total_palette[4]]\n",
    "\n",
    "# Create a dataframe with b_T_Sol values\n",
    "data_a_C_s1 = pd.concat([model_m1_s1[['a_C','model']],\n",
    "                        model_m2_s1[['a_C','model']],  \n",
    "                        model_m3_s1[['a_C','model']]],\n",
    "                       ignore_index=True)\n",
    "\n",
    "data_a_C_s2 = pd.concat([model_m1_s2[['a_C','model']],\n",
    "                        model_m2_s2[['a_C','model']],  \n",
    "                        model_m3_s2[['a_C','model']]],\n",
    "                       ignore_index=True)\n",
    "\n",
    "data_a_C_s3 = pd.concat([model_m1_s3[['a_C','model']],\n",
    "                        model_m2_s3[['a_C','model']],  \n",
    "                        model_m3_s3[['a_C','model']]],\n",
    "                       ignore_index=True)\n",
    "# Plot b_T_Sol values\n",
    "ploto.plot_pretty_boxplot(data_a_C_s1, \"a_C\", 'a_c_sim1', 2.35, 2.45,'${a}_C$', palette)\n",
    "ploto.plot_pretty_boxplot(data_a_C_s2, \"a_C\", 'a_c_sim2',  2.35, 2.45, '${a}_C$', palette)\n",
    "ploto.plot_pretty_boxplot(data_a_C_s3, \"a_C\", 'a_c_sim3', 2.35, 2.45, '${a}_C$', palette)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_palette = sns.color_palette(\"light:b\")\n",
    "\n",
    "# Create a palette dictionary matching the model names in the data\n",
    "palette = [total_palette[0], total_palette[2], total_palette[4]]\n",
    "\n",
    "# Create a dataframe with b_T_Sol values\n",
    "data_b_C_T_s1 = pd.concat([model_m2_s1[['b_C_T','model']],  \n",
    "                        model_m3_s1[['b_C_T','model']]],\n",
    "                       ignore_index=True)\n",
    "\n",
    "data_b_C_T_s2 = pd.concat([model_m2_s2[['b_C_T','model']],  \n",
    "                        model_m3_s2[['b_C_T','model']]],\n",
    "                       ignore_index=True)\n",
    "\n",
    "data_b_C_T_s3 = pd.concat([model_m2_s3[['b_C_T','model']],  \n",
    "                        model_m3_s3[['b_C_T','model']]],\n",
    "                       ignore_index=True)\n",
    "# Plot b_C_T values\n",
    "ploto.plot_pretty_boxplot(data_b_C_T_s1, \"b_C_T\", \"b_C_T_sim1\", -0.03, 0.17, '${b}_{c,t}$', palette)\n",
    "ploto.plot_pretty_boxplot(data_b_C_T_s2, \"b_C_T\", \"b_C_T_sim2\", 0.57, 0.77,'${b}_{c,t}$', palette)\n",
    "ploto.plot_pretty_boxplot(data_b_C_T_s3, \"b_C_T\", \"b_C_T_sim3\", 0.57, 0.77, '${b}_{c,t}$', palette)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_palette = sns.color_palette(\"light:b\")\n",
    "\n",
    "# Create a palette dictionary matching the model names in the data\n",
    "palette = [total_palette[0], total_palette[2], total_palette[4]]\n",
    "\n",
    "# Create a dataframe with b_T_Sol values\n",
    "data_b_C_S_s1 = pd.concat([model_m1_s1[['b_C_S','model']],  \n",
    "                        model_m3_s1[['b_C_S','model']]],\n",
    "                       ignore_index=True)\n",
    "\n",
    "data_b_C_S_s2 = pd.concat([model_m1_s2[['b_C_S','model']],  \n",
    "                        model_m3_s2[['b_C_S','model']]],\n",
    "                       ignore_index=True)\n",
    "\n",
    "data_b_C_S_s3 = pd.concat([model_m1_s3[['b_C_S','model']],  \n",
    "                        model_m3_s3[['b_C_S','model']]],\n",
    "                       ignore_index=True)\n",
    "# Plot b_T_Sol values\n",
    "ploto.plot_pretty_boxplot(data_b_C_S_s1, \"b_C_S\", \"b_C_S_sim1\", 0.175, 0.525, '${b}_{c,s}$', palette)\n",
    "ploto.plot_pretty_boxplot(data_b_C_S_s2, \"b_C_S\", \"b_C_S_sim2\", -0.025, 0.325,'${b}_{c,s}$', palette)\n",
    "ploto.plot_pretty_boxplot(data_b_C_S_s3, \"b_C_S\", \"b_C_S_sim3\", 0.275, 0.625, '${b}_{c,s}$', palette)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 350x175 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_palette = sns.color_palette(\"light:b\")\n",
    "\n",
    "# Create a palette dictionary matching the model names in the data\n",
    "palette = [total_palette[0], total_palette[2], total_palette[4]]\n",
    "\n",
    "# Create a dataframe with b_T_Sol values\n",
    "data_sigma_s1 = pd.concat([model_m1_s1[['sigma','model']],\n",
    "                        model_m2_s1[['sigma','model']],  \n",
    "                        model_m3_s1[['sigma','model']]],\n",
    "                       ignore_index=True)\n",
    "\n",
    "data_sigma_s2 = pd.concat([model_m1_s2[['sigma','model']],\n",
    "                        model_m2_s2[['sigma','model']],  \n",
    "                        model_m3_s2[['sigma','model']]],\n",
    "                       ignore_index=True)\n",
    "\n",
    "data_sigma_s3 = pd.concat([model_m1_s3[['sigma','model']],\n",
    "                        model_m2_s3[['sigma','model']],  \n",
    "                        model_m3_s3[['sigma','model']]],\n",
    "                       ignore_index=True)\n",
    "# Plot b_T_Sol values\n",
    "ploto.plot_pretty_boxplot(data_sigma_s1, \"sigma\", 'sigma_sim1', 0.375, 0.715, r'${{\\sigma}}$', palette)\n",
    "ploto.plot_pretty_boxplot(data_sigma_s2, \"sigma\", 'sigma_sim2', 0.375, 0.715, r'${{\\sigma}}$', palette)\n",
    "ploto.plot_pretty_boxplot(data_sigma_s3, \"sigma\", 'sigma_sim3', 0.375, 0.715, r'${{\\sigma}}$', palette)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "mercury",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
